Jobs Companies HKEX Vice President - LME Data Platform

Sobre esta vaga de Vice President - LME Data Platform na HKEX

HKEX · Presencial · CN-Shenzhen-HyQ

Location:

CN-Shenzhen-HyQ

Shift:

Standard - 40 Hours (China)

Scheduled Weekly Hours:

40

Worker Type:

Permanent

Job Summary:

Lead the architecture, design, and technical strategy for the company's open-source data platform. Make the end-to-end technical vision — from ingestion to analytics — while mentoring a team of data platform engineers. This is a hands-on leadership role responsible for design the blueprints and write critical-path code.

Job Duties:

Responsibilities

Architecture & Strategy

  • Define the overall data platform architecture on OpenShift, covering the full lifecycle: ingestion (Kafka/Redpanda), compute (Spark, Flink, Trino), storage (MinIO, Iceberg), catalog (Polaris/Gravitino), orchestration (Airflow/Dagster), and serving (StarRocks/ClickHouse)
  • Design the Data Lakehouse architecture: open table formats (Iceberg, Delta Lake), catalog federation, multi-engine interoperability
  • Architect the real-time data path: Kafka topic design, schema registry (Apicurio/Confluent), stream processing (Flink/Spark Structured Streaming)
  • Design the analytical serving layer: OLAP engine selection (StarRocks/ClickHouse/Doris), materialized view strategy, query federation with Trino
  • Design multi-tenancy, data security (Ranger/OpenPolicyAgent), RBAC, and governance (DataHub/Atlas) across all platform layers
  • Set technical standards for Helm chart design, CI/CD pipelines, and GitOps (ArgoCD/Flux) workflows
  • Own data lifecycle management: hot/warm/cold tiering across MinIO, compaction, retention, and GDPR/deletion compliance

Technical Leadership

  • Lead a team of 3–6 data platform engineers; run code reviews, design reviews, and sprint planning
  • Establish engineering best practices: testing, observability (OpenTelemetry, Prometheus, Grafana, Loki), incident response, runbooks
  • Partner with data engineering, analytics, and business teams to translate their needs into platform capabilities
  • Define platform SLOs/SLIs across freshness, latency, availability, and durability; drive the on-call rotation and incident post-mortems

Hands-on Engineering

  • Build and maintain the core OpenShift infrastructure: operators, Helm charts, namespaces, RBAC, network policies
  • Develop Spark and Flink job frameworks, tuning guides, workload scheduling (YuniKorn/Volcano)
  • Implement the data mesh or data product model: domain ownership, self-serve data infrastructure, federated governance
  • Performance-optimize across the stack: Kafka throughput, Spark shuffle, Iceberg compaction, Trino query planning, OLAP cold reads

Required Skills & Experience

  • 10 + years in data/platform engineering, with 3+ years as architect or tech lead
  • Deep Kubernetes/OpenShift: operators, Helm, CRDs, admission webhooks, SCC, multi-tenancy at production scale
  • Expert-level streaming: Kafka/Redpanda internals (partitioning, consumer groups, exactly-once semantics), schema registry, Kafka Connect
  • Expert-level batch & streaming compute: Spark internals (Catalyst, Tungsten, AQE, shuffle, dynamic allocation), Flink or Spark Structured Streaming
  • Strong open table format knowledge: Iceberg and/or Delta Lake — table format internals, metadata evolution, partitioning transforms, maintenance, catalog integration (Polaris, Gravitino, Nessie, or Unity Catalog)
  • Hands-on with federated query engines: Trino (coordinator/worker architecture, connector ecosystem, fault-tolerant execution mode)
  • Solid OLAP knowledge: StarRocks, ClickHouse, or Apache Doris — primary key models, materialized views, query optimization
  • Production MinIO/S3-compatible storage at scale: erasure coding, multi-site replication, IAM, tiering
  • Pipeline orchestration: Airflow (DAG design, sensors, dynamic task mapping) or Dagster
  • Infrastructure-as-code (Terraform/Pulumi/Crossplane) and GitOps (ArgoCD/Flux)
  • Fluent in at least one JVM language (Scala/Java) and Python

Nice to Have

  • Experience deploying dbt (data build tool) with Trino or Spark adapters for data transformation
  • Data governance hands-on: DataHub or Apache Atlas for lineage, glossary, and metadata search
  • Data security: Apache Ranger or OpenPolicyAgent for fine-grained access control
  • Open-source contributions to any of the above projects

Company Introduction:

ITD SZ

港交所科技(深圳)有限公司,是2016年12月28日于深圳市前海自贸区成立的外商独资企业。

作为港交所的技术子公司,港交所科技(深圳)有限公司主要是为集团及其附属公司提供计算机软件、计算机硬件、信息系统、云存储、云计算、物联网和计算机网络的开发、技术服务、技术咨询、技术转让;经济信息咨询、企业管理咨询、商务信息咨询、商业信息咨询、信息系统设计、集成、运行维护;数据库管理、大数据分析;以承接服务外包方式提供系统应用管理和维护、信息技术支持管理、数据处理等信息技术和业务流程外包服务。

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Sobre a HKEX

Hong Kong Exchanges and Clearing Limited (HKEX) is a publicly-traded company (HKEX Stock Code:388) and one of the world’s leading global exchange groups, offering a range of equity, derivative, commodity, fixed income and other financial markets, products and services, including the London Metals Exchange. As a superconnector and gateway between East and West, HKEX facilitates the two-way flow of capital, ideas and dialogue between China and the rest of world, through its pioneering Connect schemes, increasingly diversified product ecosystem and its deep, liquid and international markets. HKEX is a purpose-led organisation which, across its business and through the work of HKEX Foundation, s

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